The parcellation-based connectome: limitations and extensions

de Reus, Marcel A.; van den Heuvel, Martijn P.

doi:10.1016/j.neuroimage.2013.03.053

Cited by 282Functional Brain Connectivity StudiesAdvanced Neuroimaging Techniques and ApplicationsComplex Network Analysis Techniques

The parcellation-based connectome: limitations and extensions

de Reus, Marcel A., van den Heuvel, Martijn P.·2013·NeuroImage

DOI 10.1016/j.neuroimage.2013.03.053

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Abstract

The human connectome is an intricate system of interconnected elements, providing the basis for integrative brain function. An essential step in the macroscopic mapping and examination of this network of structural and functional interactions is the subdivision of the brain into large-scale regions. Parcellation approaches used for the formation of macroscopic brain networks include application of predefined anatomical templates, randomly generated templates and voxel-based divisions. In this review, we discuss the use of such parcellation approaches for the examination of connectome characteristics. We specifically address the impact of the choice of parcellation scheme and resolution on the estimation of the brain's topological and spatial network features. Although organizational principles of functional and structural brain networks appear to be largely independent of the adopted parcellation approach, quantitative measures of these principles may be significantly modulated. Future parcellation-based connectome studies might benefit from the adoption of novel network tools and promising advances in connectivity-based parcellation approaches.

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Currently, there is no consensus about which brain parcellation technique could be most useful.
“Currently, there is no consensus about which brain parcellation technique could be most useful (de Reus and Van den Heuvel, 2013; Yeh et al., 2020; Zalesky et al., 2012).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as de Reus and Van den Heuvel, 2013
Selection of a gray matter parcellation scheme is the first essential consideration when constructing a structural connectivity matrix and has been shown to be highly consequential in connectome analysis.
“Selection of a gray matter parcellation scheme (as described in Section 4.2) is the first essential consideration when constructing a structural connectivity matrix, and it has been shown to be highly consequential in connectome analysis (de Reus and Van den Heuvel, 2013; Yeh et al., 2020; Zalesky et al., 2012).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as de Reus and Van den Heuvel, 2013
Global topological metrics for structural and functional networks show stability across different parcellation schema of similar density, but vary considerably as a function of network size.
“Global topological metrics for structural and functional networks show stability across different parcellation schema of similar density, but vary considerably as a function of network size (de Reus and van den Heuvel, 2013; Fornito et al., 2010; Zalesky et al., 2010).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as de Reus and van den Heuvel, 2013

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Authors: de Reus, M. A., & van den Heuvel, M. P.
Venue: NeuroImage
Publisher: Elsevier BV
Published: 2013-10
Volume: 80
Pages: 397-404
ISSN: 1053-8119 (ISSN-L)
DOI: 10.1016/j.neuroimage.2013.03.053
OpenAlex: W1998095942
Cited by: 282
References: 113
Citations by year: 2026: 7 · 2025: 12 · 2024: 5 · 2023: 20 · 2022: 26 · 2021: 25 · 2020: 17 · 2019: 23 · 2018: 22 · 2017: 33 · 2016: 32 · 2015: 29 · 2014: 23 · 2013: 8
FWCI: 16.75
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: NeuroImage (publishedVersion)
PubMed (publishedVersion)
Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
Pure Amsterdam UMC (submittedVersion)
Data Archiving and Networked Services (DANS) (submittedVersion)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
Keywords: human connectome, brain parcellation, structural connectivity, functional connectivity, anatomical template, network topology, connectivity-based parcellation
MeSH terms: Animals, Brain, Humans, Magnetic Resonance Imaging, Models, Anatomic, Models, Neurological, Nerve Net, Connectome

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The parcellation-based connectome: limitations and extensions

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